National Weather Center Colloquium

Thunderstorms Don’t Get Butterflies

Dr. Dale Durran

22 March 2016, 4:00 PM

The weather will evolve differently from that predicted by a perfect forecast model if the initial state provided to the model differs even slightly from that for the atmosphere. Lorenz showed that confining errors in the initial state to ever smaller scales, possibly even down to the size of a butterfly, did not significantly extend the time over which his highly idealized model exhibited predictive skill. Nevertheless, recent work with Lorenz’s model has shown that initial errors at extremely small scales are not likely to impose a practical limit on forecast accuracy because they would be swamped by minor relative errors in the initial conditions at much larger scales. Employing detailed simulations of the error growth in collections of thunderstorms, we show that similar conclusions about the importance of larger scales apply to the propagation of initial-condition errors in much more realistic settings. Our results imply that minimizing initial errors on scales around 100 km is more likely to extend the accuracy of squall-line forecasts than would potentially expensive efforts to initialize smaller-scale atmospheric circulations. We also demonstrate that squall lines, triggered in an environment with no initial background circulations, can generate a background mesoscale kinetic energy spectrum roughly similar to that observed in the atmosphere.